Hands on Machine Learning Project – Auto Image Captioning for Social Media Overview

The Hands-on Machine Learning Project – Auto Image Captioning for Social Media course offers practical experience in building an automated image captioning system. Suitable for beginners and intermediates, it covers text and image preprocessing, deep learning model training, and deployment using Streamlit and AWS EC2. By course end, you’ll be equipped to create and deploy a custom image captioning model for social media.

Learning Outcomes

• Understand the fundamental concepts of machine learning and image captioning.
• Gain hands-on experience with Python libraries commonly used in machine learning.
• Learn how to access and preprocess caption and image datasets for training purposes.
• Develop skills in text tokenisation and sequence generation for deep learning models.
• Build and train a neural network model for image captioning.
• Evaluate and refine your model’s performance on test datasets.
• Create and customise a Streamlit application for user-friendly model interaction.
• Deploy a machine learning application on AWS EC2 for real-world use.
• Understand how to generate predictions using your deployed Streamlit app.
• Master the end-to-end process of building and deploying a machine learning model for social media.

Who Is This Course For

This course is perfect for anyone eager to apply machine learning to social media or expand their skills in deep learning and model deployment. It’s tailored for data enthusiasts, aspiring machine learning engineers, and developers who want hands-on experience building practical AI applications. Whether you’re a beginner with some programming knowledge or an intermediate learner aiming to specialise in machine learning, this course gives you the tools and knowledge you need to advance your career in AI-driven projects.

Eligibility Requirements

To enrol in this course, learners should have a basic understanding of programming, preferably in Python. Familiarity with fundamental concepts in machine learning is beneficial but not mandatory, as the course will cover essential concepts needed for the project. Access to a computer with internet connectivity is necessary for coding exercises and deployment tasks.

Entry Requirements

• Age Requirement: Applicants must be aged 16 or above, allowing both young learners and adults to engage in this educational pursuit.
• Academic Background: There are no specific educational prerequisites, opening the door to individuals from diverse academic histories.
• Language Proficiency: A good command of the English language is essential for comprehension and engagement with the course materials.
• Numeracy Skills: Basic numeracy skills are required to effectively understand and work with course-related information. 

Why Choose Us

• Affordable, engaging & high-quality e-learning study materials;
• Tutorial videos/materials from the industry-leading experts;
• Study in a user-friendly, advanced online learning platform;
• Efficient exam systems for the assessment and instant result;
• The UK & internationally recognised accredited
• Access to course content on mobile, tablet or desktop from anywhere, anytime;
• The benefit of career advancement opportunities;
• 24/7 student support via email.
  

Career Path

Upon completing this course, you’ll be prepared for roles in machine learning and AI, such as a machine learning engineer or data scientist. You’ll gain skills in image processing, natural language processing, and AI integration, making you a strong candidate for positions in software development and social media technology, where automated image captioning is valuable.